Skip to Main content Skip to Navigation
Conference papers

Adaptation of a Term Extractor to Arabic Specialised Texts: First Experiments and Limits

Abstract : In this paper, we present an adaptation to Modern Standard Arabic of a French and English term extractor. The goal of this work is to reduce the lack of resources and NLP tools for Arabic language in specialised domains. The adaptation firstly focuses on the description of extraction processes similar to those already defined for French and English while considering the morpho-syntactic specificity of Arabic. Agglutination phenomena are further taken into account in the term extraction process. The current state of the adapted system was evaluated on a medical text corpus. 400 maximal candidate terms were examined, among which 288 were correct (72% precision). An error analysis shows that term extraction errors are first due to Part-of-Speech tagging errors and the difficulties induced by non-diacritised texts, then to remaining agglutination phenomena.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01771875
Contributor : Limsi Publications <>
Submitted on : Friday, April 20, 2018 - 4:53:19 AM
Last modification on : Wednesday, September 16, 2020 - 5:27:40 PM

Identifiers

  • HAL Id : hal-01771875, version 1

Citation

Wafa Neifar, Thierry Hamon, Pierre Zweigenbaum, Mariem Ellouze Khemakhem, Lamia Hadrich Belguith. Adaptation of a Term Extractor to Arabic Specialised Texts: First Experiments and Limits. International Conference on Intelligent Text Processing and Computational Linguistics, Springer, Jan 2016, Konya, Turkey. ⟨hal-01771875⟩

Share

Metrics

Record views

125